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Author: Yandong Wang
Committee
Chair: Prof. Alan Kaminsky
Reader: Prof. Stanislaw Radziszowski
Observer: Prof. James Heliotis
Title: NVIDIA CUDA Architecture-Based Parallel Incomplete SAT Solver
Defense Date: June 21, 2010
Abstract: The contribution of this project is that it incorporated the advantage of the application of stochastic local search and genetic algorithm to the SAT solvers and the superior parallel computing capability of CUDA GPU, designed a highly efficient CUDA architecture-based incomplete SAT solver that couples cellular genetic algorithm and random walk local search. The measurement results by testing Uniform Random-3-SAT SAT benchmarks present that this novel SAT solver is able to give out an efficient running time performance and ideal scalability.
Proposal: proposal.pdf
Report: report.pdf
Defense Presentation: presentation.pdf
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